Attentionviz: A global view of transformer attention
Transformer models are revolutionizing machine learning, but their inner workings remain
mysterious. In this work, we present a new visualization technique designed to help …
mysterious. In this work, we present a new visualization technique designed to help …
Explainability of Vision Transformers: A Comprehensive Review and New Perspectives
Transformers have had a significant impact on natural language processing and have
recently demonstrated their potential in computer vision. They have shown promising results …
recently demonstrated their potential in computer vision. They have shown promising results …
Hierarchical local-global transformer for temporal sentence grounding
This article studies the multimedia problem of temporal sentence grounding (TSG), which
aims to accurately determine the specific video segment in an untrimmed video according to …
aims to accurately determine the specific video segment in an untrimmed video according to …
Explanatory models in neuroscience, Part 1: Taking mechanistic abstraction seriously
Despite the recent success of neural network models in mimicking animal performance on
various tasks, critics worry that these models fail to illuminate brain function. We take it that a …
various tasks, critics worry that these models fail to illuminate brain function. We take it that a …
LVLM-Intrepret: An Interpretability Tool for Large Vision-Language Models
In the rapidly evolving landscape of artificial intelligence, multi-modal large language
models are emerging as a significant area of interest. These models, which combine various …
models are emerging as a significant area of interest. These models, which combine various …
Signet: A siamese graph convolutional network for multi-class urban change detection
Y Zhou, J Wang, J Ding, B Liu, N Weng, H Xiao - Remote Sensing, 2023 - mdpi.com
Detecting changes in urban areas presents many challenges, including complex features,
fast-changing rates, and human-induced interference. At present, most of the research on …
fast-changing rates, and human-induced interference. At present, most of the research on …
Multi-Dataset Comparison of Vision Transformers and Convolutional Neural Networks for Detecting Glaucomatous Optic Neuropathy from Fundus Photographs
EE Hwang, D Chen, Y Han, L Jia, J Shan - Bioengineering, 2023 - mdpi.com
Glaucomatous optic neuropathy (GON) can be diagnosed and monitored using fundus
photography, a widely available and low-cost approach already adopted for automated …
photography, a widely available and low-cost approach already adopted for automated …
Recasting Generic Pretrained Vision Transformers As Object-Centric Scene Encoders For Manipulation Policies
J Qian, A Panagopoulos, D Jayaraman - arXiv preprint arXiv:2405.15916, 2024 - arxiv.org
Generic re-usable pre-trained image representation encoders have become a standard
component of methods for many computer vision tasks. As visual representations for robots …
component of methods for many computer vision tasks. As visual representations for robots …
Universal Deoxidation of Semiconductor Substrates Assisted by Machine Learning and Real-Time Feedback Control
C Shen, W Zhan, J Tang, Z Wu, B Xu… - … Applied Materials & …, 2024 - ACS Publications
Substrate oxidation is inevitable when exposed to ambient atmosphere during
semiconductor manufacturing, which is detrimental to the fabrication of state-of-the-art …
semiconductor manufacturing, which is detrimental to the fabrication of state-of-the-art …
GRACE: Unveiling Gene Regulatory Networks With Causal Mechanistic Graph Neural Networks in Single-Cell RNA-Sequencing Data
JC Wang, YJ Chen, Q Zou - IEEE Transactions on Neural …, 2024 - ieeexplore.ieee.org
Reconstructing gene regulatory networks (GRNs) using single-cell RNA sequencing (scRNA-
seq) data holds great promise for unraveling cellular fate development and heterogeneity …
seq) data holds great promise for unraveling cellular fate development and heterogeneity …